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Microsoft AutoGen v0.4: A turning point toward more intelligent AI agents for enterprise developers
AutoGen represents Microsoft’s latest attempt to address the challenges of building multi-agent systems for enterprise applications. This article explores what this means for the state of agentic AI today, and how it compares to other major frameworks like LangChain and CrewAI. This article unpacks the implications of AutoGen’s update, explores its standout features, and situates it within the broader landscape of AI agent frameworks, helping developers understand what’s possible and where the industry is headed.
This article unpacks the implications of AutoGen’s update, explores its standout features, and situates it within the broader landscape of AI agent frameworks, helping developers understand what’s possible and where the industry is headed. While LangChain has recently introduced “ambient agents” for background task automation (see our story on this, which includes an interview with founder Harrison Chase), AutoGen’s strength lies in its extensibility—allowing developers to build custom tools and extensions tailored to specific use cases. However, a big point made by Witteveen is that these frameworks are still mainly used as great places to build prototypes and experiment, and that many developers port their work over to their own custom environments and code (including the Pydantic library for Python for example) when it comes to actual deployment.
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